title: An evaluation of the PacBio RS platform for sequencing and de novo assembly of a chloroplast genome.
abstract: BACKGROUND
  Second generation sequencing has permitted detailed sequence characterisation at the whole genome level of a growing number of non-model organisms, but the data produced have short read-lengths and biased genome coverage leading to fragmented genome assemblies. The PacBio RS long-read sequencing platform offers the promise of increased read length and unbiased genome coverage and thus the potential to produce genome sequence data of a finished quality containing fewer gaps and longer contigs. However, these advantages come at a much greater cost per nucleotide and with a perceived increase in error-rate. In this investigation, we evaluated the performance of the PacBio RS sequencing platform through the sequencing and de novo assembly of the Potentilla micrantha chloroplast genome.
  
  
  RESULTS
  Following error-correction, a total of 28,638 PacBio RS reads were recovered with a mean read length of 1,902 bp totalling 54,492,250 nucleotides and representing an average depth of coverage of 320× the chloroplast genome. The dataset covered the entire 154,959 bp of the chloroplast genome in a single contig (100% coverage) compared to seven contigs (90.59% coverage) recovered from an Illumina data, and revealed no bias in coverage of GC rich regions. Post-assembly the data were largely concordant with the Illumina data generated and allowed 187 ambiguities in the Illumina data to be resolved. The additional read length also permitted small differences in the two inverted repeat regions to be assigned unambiguously.
  
  
  CONCLUSIONS
  This is the first report to our knowledge of a chloroplast genome assembled de novo using PacBio sequence data. The PacBio RS data generated here were assembled into a single large contig spanning the P. micrantha chloroplast genome, with a higher degree of accuracy than an Illumina dataset generated at a much greater depth of coverage, due to longer read lengths and lower GC bias in the data. The results we present suggest PacBio data will be of immense utility for the development of genome sequence assemblies containing fewer unresolved gaps and ambiguities and a significantly smaller number of contigs than could be produced using short-read sequence data alone.
authors.affiliation: Research and Innovation Centre, Fondazione Edmund Mach, Via E, Mach 1, 38010 San Michele all'Adige, Italy. dan.sargent@fmach.it.
authors.forename: Marco
authors.initials: M
authors.lastname: Ferrarini
authors.forename: Marco
authors.initials: M
authors.lastname: Moretto
authors.forename: Judson A
authors.initials: JA
authors.lastname: Ward
authors.forename: Nada
authors.initials: N
authors.lastname: Šurbanovski
authors.forename: Vladimir
authors.initials: V
authors.lastname: Stevanović
authors.forename: Lara
authors.initials: L
authors.lastname: Giongo
authors.forename: Roberto
authors.initials: R
authors.lastname: Viola
authors.forename: Duccio
authors.initials: D
authors.lastname: Cavalieri
authors.forename: Riccardo
authors.initials: R
authors.lastname: Velasco
authors.forename: Alessandro
authors.initials: A
authors.lastname: Cestaro
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Sargent
mesh_terms: D001482:Base Composition / Q000235:genetics; D001483:Base Sequence; D030541:Databases, Genetic; D054628:Genome, Chloroplast / Q000235:genetics*; D031987:Potentilla / Q000235:genetics*; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software